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Mlops Machine Learning Engineer Jobs in Issaquah, WA

Hive

Staff Machine Learning Engineer

Seattle, WA · On-site

$200K - $300K/yr

Staff Machine Learning Engineer In order to execute our vision, we need to grow our team of best-in-class machine learning engineers. We are looking for developers who are excited about staying at ...

Axon

Senior Machine Learning Engineer

Seattle, WA · On-site

$139K - $183K/yr

As a Machine Learning Engineer at Axon , you'll help build AI solutions that are transforming public safety and advancing our mission to Protect Life . You'll work alongside talented ML engineers and ...

Zoom

Sr. Machine Learning Engineer - AI

Seattle, WA · On-site

$157.44 - $236.20/hr

As a Machine Learning Engineer specializing in knowledge graphs, you will work closely with cross-functional teams to design, implement, and optimize algorithms and models that enable efficient ...

Unitytech

Machine Learning Engineer, New Grad

Bellevue, WA · On-site +1

$117K - $152K/yr

We're looking for a Machine Learning Engineer to join our Offline Infrastructure team. This is an ideal role for a recent university graduate who is excited to work on large-scale systems and apply ...

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All JobsMlops Machine Learning Engineer JobsMlops Machine Learning Engineer Jobs in Issaquah, WA

Mlops Machine Learning Engineer information

See Issaquah, WA salary details

$36.3K

$148.5K

$223.2K

How much do mlops machine learning engineer jobs pay per year?

As of Sep 3, 2026, the average yearly pay for mlops machine learning engineer in Issaquah, WA is $148,515.00, according to ZipRecruiter salary data. Most workers in this role earn between $117,100.00 and $178,800.00 per year, depending on experience, location, and employer.

What does an MLOps machine learning engineer do?

An MLOps Machine Learning Engineer bridges the gap between data science and IT operations by developing, deploying, and maintaining machine learning models in production environments. They are responsible for automating workflows, managing model versioning, monitoring performance, and ensuring scalability and reliability of ML systems. Their work enables organizations to deploy machine learning solutions efficiently and consistently, making it easier to update and manage models as business needs evolve.

What are the key skills and qualifications needed to thrive as an MLOps machine learning engineer?

To thrive as an MLOps Machine Learning Engineer, you need a strong background in machine learning concepts, software engineering, and cloud infrastructure, typically supported by a degree in computer science or a related field. Familiarity with tools like Docker, Kubernetes, CI/CD pipelines, cloud platforms (AWS, GCP, Azure), and certifications such as Google Professional Machine Learning Engineer are highly beneficial. Strong problem-solving abilities, collaboration, and communication skills help you work effectively across data science and engineering teams. These skills are essential for reliably deploying, monitoring, and maintaining scalable machine learning solutions in production environments.

How does an MLOps machine learning engineer typically collaborate with data scientists and software engineers during the deployment of machine learning models?

An MLOps Machine Learning Engineer acts as a bridge between data scientists and software engineers, ensuring machine learning models transition smoothly from development to production. They often work closely with data scientists to understand model requirements, data pipelines, and performance metrics, while also collaborating with software engineers to integrate models into scalable systems. Regular communication, shared documentation, and joint troubleshooting sessions are common, as the role requires aligning model performance with system reliability and maintainability. This collaborative environment helps ensure that models are robust, scalable, and impactful in real-world applications.

What is the difference between Mlops Machine Learning Engineer vs Data Scientist?

AspectMlops Machine Learning EngineerData Scientist
Required CredentialsBachelor's or master's in CS, data science, or related fields; certifications in cloud platforms or MLOps toolsBachelor's or master's in statistics, data science, or related fields; certifications in data analysis or machine learning
Work EnvironmentFocus on deploying, maintaining, and scaling ML models in production environmentsFocus on data analysis, model development, and insights generation
Employer & Industry UsageTech companies, startups, enterprises implementing ML solutionsResearch institutions, analytics firms, tech companies for data insights

While both roles involve machine learning, Mlops Machine Learning Engineers specialize in deploying and maintaining models in production, ensuring scalability and reliability. Data Scientists primarily focus on developing models and analyzing data to generate insights. The roles often overlap but differ in their core responsibilities and work environments.

Are MLOps machine learning engineers in demand?

MLOps machine learning engineers are in high demand due to the increasing adoption of AI and machine learning across industries. They are needed to develop, deploy, and maintain scalable ML systems, often requiring skills in cloud platforms, automation, and tools like Docker and Kubernetes. The role offers strong job growth prospects and competitive salaries.

Do MLOps Machine Learning Engineers need a degree?

MLOps Machine Learning Engineers typically do not require a formal degree but often have a background in computer science, data science, or related fields. Practical skills in machine learning, cloud platforms, and tools like Docker, Kubernetes, and CI/CD pipelines are highly valued. Certifications and hands-on experience can also enhance job prospects.

What are popular job titles related to Mlops Machine Learning Engineer jobs in Issaquah, WA?

For Mlops Machine Learning Engineer jobs in Issaquah, WA, the most frequently searched job titles are:

What job categories do people searching Mlops Machine Learning Engineer jobs in Issaquah, WA look for?

The top searched job categories for Mlops Machine Learning Engineer jobs in Issaquah, WA are:

What cities near Issaquah, WA are hiring for Mlops Machine Learning Engineer jobs?

Cities near Issaquah, WA with the most Mlops Machine Learning Engineer job openings:

Mlops Machine Learning Engineer jobs near you

Staff Machine Learning Engineer

Hive

Seattle, WA • On-site

$200K - $300K/yr

Full-time

Medical, Dental, Vision, PTO

Re-posted 6 days ago

Job description

About Hive
Hive is the leading provider of cloud-based AI solutions to understand, search, and generate content, and is trusted by hundreds of the world's largest and most innovative organizations. The company empowers developers with a portfolio of best-in-class, pre-trained AI models, serving billions of customer API requests every month. Hive also offers turnkey software applications powered by proprietary AI models and datasets, enabling breakthrough use cases across industries. Together, Hive's solutions are transforming content moderation, brand protection, sponsorship measurement, context-based ad targeting, and more.
Hive has raised over $120M in capital from leading investors, including General Catalyst, 8VC, Glynn Capital, Bain & Company, Visa Ventures, and others. We have over 250 employees globally in our San Francisco, Seattle, and Delhi offices. Please reach out if you are interested in joining the future of AI!
Staff Machine Learning Engineer
In order to execute our vision, we need to grow our team of best-in-class machine learning engineers. We are looking for developers who are excited about staying at the forefront of deep learning technology, prototyping state-of-the-art neural net models and launching these models into production. We value hard workers who have no qualms working with terabyte-scale datasets, who are interested in learning new technologies at all levels of the machine learning stack, and who move fast and take ownership of their projects. Our ideal candidate has experience creating a working machine learning-powered project from the ground up, contributes innovative ideas and ingenious implementations to the team, and is capable of planning out scalable, maintainable data pipelines.
Responsibilities
  • Everything involved in applying a ML model to a production use case, including designing and coding up the neural network, gathering and refining data, training and tuning the model, deploying it at scale with high throughput and uptime, and analyzing the results in the wild in order to continuously update and improve accuracy and speed
  • Write and maintain scalable, performant code that can be shared across platforms
  • Contribute meaningfully to the product and core backend systems by suggesting and executing improvements
  • Improve engineering standards, tooling, and processes
  • Develop novel, accurate, and performant ML algorithms for use at scale
  • Conduct metric-driven research experiments to improve model performance
  • Provide mentorship to and help onboard ML engineers
  • Lead cross-functional collaboration with other teams
  • Contribute to defining strategic direction, planning the roadmap
  • Maintain awareness of industry best practices for data maintenance handling as it relates to your role
  • Adhere to policies, guidelines and procedures pertaining to the protection of information assets
  • Report actual or suspected security and/or policy violations/breaches to an appropriate authority

Minimum Requirements
  • You have a Bachelor's Degree in computer science or a related field
  • You have 8+ years of experience building web applications
  • You have successfully implemented highly-available distributed systems/microservices
  • You have delivered scalable backend APIs
  • You have strong interpersonal and communication skills with a bias towards action
  • You have experience writing code and training across distributed systems
  • You have the ability to understand and make well-reasoned tradeoffs in designing features
  • You are an expert in machine learning frameworks, such as PyTorch or Tensorflow
  • You are an expert in scripting languages such as Python and/or shell scripts, particularly for data analysis
  • You are a subject matter expert in at least one focus area of machine learning, such as computer vision or natural language processing
  • You can lead end to end development of new products

Who We Are
We are a group of ambitious individuals who are passionate about creating a revolutionary AI company. At Hive, you will have a steep learning curve and an opportunity to contribute to one of the fastest growing AI start-ups in San Francisco. The work you do here will have a noticeable and direct impact on the development of the company.
Thank you for your interest in Hive and we hope to meet you soon!
The current expected base salary for this position ranges from $200,000 - $300,000. Actual compensation may vary depending on a number of factors, including a candidate's qualifications, skills, competencies and experience, and location. Base pay is one part of the total compensation package that is provided to compensate and recognize employees for their work; stock options may be offered in addition to the range provided here.
Employees are eligible to participate in a number of Company-sponsored benefits, including health, vision and dental insurance. Employees are also eligible to participate in a gym membership as part of our commitment to employee wellness. In addition, employees will be entitled to paid vacation in accordance with the Company's vacation policy.
Hired applicant may receive an equity grant in the form of an option to purchase stock in the future for a specified price.
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.

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